Multicoil MRI has been used for many years to non-invasively examine the nuclear magnetic resonance (NMR) spin density distribution within three dimensional objects or volumes. Typically, using existing MRI data acquisition methods and data processing methods, the object under investigation is placed in a static magnetic field B0 and is energized by an alternating magnetic field B1. The frequency of the alternating magnetic field B1 is selected as the Larmor frequency (the natural nuclear magnetic resonant frequency) for the atomic species of interest. The Larmor frequency depends upon the magnitude of the static field B0, among other factors. A number of well-known MRI applications have detected the hydrogen proton spin density, although it is possible to image carbon, potassium and other atomic species with certain nuclear spin properties.
Typically, using existing MRI data acquisition methods and data processing methods, magnetic field gradients are applied across the object under investigation, either during or after the application of the alternating field B1. These magnetic field gradients cause the frequency of the NMR signal to vary in a predictable way along the various spatial dimensions of the object under investigation. Thus, in the prior state of the art of MRI, spatial localization is accomplished by frequency and/or phase encoding of the object through the application of controlled magnetic field gradients.
Some existing MRI devices are designed to use multiple coils during data acquisition, and some conventional MRI data processing methods exploit the differences between the individual coil fields to enhance the spatial resolution and quality of the NMR image. See for example U.S. Pat. No. 6,160,398. However, all existing MRI devices, MRI data acquisition methods and MRI data processing methods derive some or all of the spatial information required for imaging in three dimensions through the application of magnetic gradient fields.
While existing MRI devices, data acquisition methods and data processing methods may be suitable for the particular purpose to which they address, they are not as suitable for performing three dimensional magnetic resonance imaging in a static magnetic field without the application of controlled static magnetic field gradients.
A primary limitation of existing MRI devices and methods is the requirement to generate and control gradients in the static field B0. The generation and control of such gradients requires specially designed gradient field coils, and these coils are typically only effective when employed in certain constrained geometries. For example, in medical MRI, a great deal of research has been undertaken to design and construct the gradient coils for specific MRI scanner designs, and the gradient coil assemblies represent a significant portion of the scanner's expense. Most conventional MRI scanners use gradient coils that surround the object under investigation in order to produce approximately linear field gradients.
For many potential applications of three-dimensional MRI, the requirement to generate and control static field gradients is either impractical or prohibitively expensive. For example, in the investigation of subsurface groundwater distributions via surface coil NMR measurements, the generation of significant gradients in the Earth's magnetic field at operationally significant depths would require large amounts of power and complex arrays of magnetic field antennae. The imaging of other large fixed objects, such as bridge supports and building foundations, is similarly constrained by power requirements and the difficulty in generating and controlling static field gradients in three dimensions. Other potential applications of MRI, such as industrial non-destructive evaluation of raw materials, are not presently commercially viable due to the expense and geometrical constraints associated with conventional gradient-based MRI scanners.
Surface NMR data acquisition methods and data processing methods have been used for many years to detect and localize subsurface groundwater. The existing state of the art in surface NMR utilizes a single surface coil to generate the alternating B1 field. The B1 field is transmitted with various levels of energy, and the measured NMR signals received on the same coil or a single separate coil are mathematically processed to estimate a profile for the groundwater distribution in one dimension only: depth. While existing surface NMR devices, data acquisition methods and data processing methods may be suitable for the particular purpose to which they address, they are not as suitable for performing three dimensional magnetic resonance imaging in a static magnetic field without the application of controlled static magnetic field gradients. Many surface NMR techniques can produce, at best, an estimate of the 1-dimensional groundwater density profile directly beneath the coil. These 1-D profile estimates are subject to a variety of errors stemming from the use of a single surface coil, and inaccurate 1-D models of the coil fields and water density profiles.
In recent years, single-coil surface NMR instruments have been developed and commercialized, and surface NMR data processing methods have been developed to characterize the distribution of groundwater in one or two dimensions. The first working surface NMR instrument was developed in the U.S.S.R. as described by Semenov et al. in USSR inventor's certificate 1,079,063, issued in 1988. The existing state of the art in surface NMR, epitomized by the commercial “Numis” brand instrument, utilizes a single surface coil to generate the alternating B1 field. The B1 field is transmitted with various levels of energy, and the measured NMR signals received on the same surface coil or a single separate surface coil are mathematically processed to estimate a profile for the groundwater distribution in one dimension only: depth. A commonly employed one-dimensional surface NMR profiling is described by Legchenko and Shushakov in “Inversion of surface NMR data” appearing in Geophysics vol. 63: 75-84 (1998), incorporated hereinto by reference.
Presently available 1-D profile estimation techniques, which are based on single coil surface NMR systems, rely on a single measurement variable: the transmitted pulse energy and its relation to tip angle, to estimate a water density profile in depth. The NMR signal amplitude at a given point in space is a sinusoidal function of the flip angle at that location. Present 1-D inversion techniques measure the NMR signal using different transmit pulse energy levels, and then fit the set of NMR amplitudes to a simplified 1-D model. To make the inversion tractable, the coil vector field lines are assumed to be parallel and confined to a cylinder directly beneath the coil, and the water density profile is assumed to vary in one dimension only.
Reliance on one dimensional modeling according to the prior art therefore engenders certain deficiencies. A first fundamental problem is that the coil field lines are very different from the assumed cylindrical model over large portions of the investigation space. The generated signal depends upon the angle between the earth's vector field and the coil's vector field. A second fundamental problem is the assumption that the water density profile varies in one dimension only. Three-dimensionally variant aquifers, which are common in nature, cannot be adequately characterized using simple 1-D models. A third fundamental problem is that even if accurate coil field models were employed and 3-D water distributions were allowed, the resulting inversion would suffer from ambiguities. The integrated NMR signal depends on the 3-D distribution of water, the coil field lines, the Earth's field direction, and the transmitted pulse energy. Varying the pulse energy alone does not provide enough information to unambiguously solve the 3-D inversion problem.
In recognition of the limitations, ambiguities and potential errors imposed by the use of a single surface coil, other researchers have investigated the possibility of multi-dimensional surface NMR investigation using one or more laterally displaced surface coils. Hertrich and Yaramanci presented a three dimensional mathematical kernal function for the surface NMR signal source in “Surface-NMR with spatially separated loops—investigations on spatial resolution” appearing in the 2nd International Workshop on the Magnetic Resonance Sounding method applied to non-invasive groundwater investigations (19-21 Nov. 2003), incorporated herein by reference. Warsa, Mohnke and Yaramanci presented a discrete approximation of a 3-D model for the surface NMR signal source in “3-D modeling and assessment of 2-D inversion of surface NMR” appearing in the 2nd International Workshop on the Magnetic Resonance Sounding method applied to non-invasive groundwater investigations (19-21 Nov. 2003), also incorporated herein by reference. Although these references are useful in the development of the present invention, they do not describe a practical method for processing multi-coil surface NMR data into useful multi-dimensional estimates of the subsurface liquid distributions, and these references explicitly acknowledge the absence of such a method.
It is also recognized that electromagnetic field noise places another limitation on the utility and reliability of the prior state of the art in surface NMR. A variety of noise processes limit the ability to detect and localize groundwater using surface NMR measurements. Prior attempts to mitigate such noise have been limited to temporal processing of the raw data from a single coil. The existing prior art in this area is described by Legchenko in “Industrial noise and processing of the magnetic resonance signal” appearing in the 2nd International Workshop on the Magnetic Resonance Sounding method applied to non-invasive groundwater investigations (19-21 Nov. 2003), incorporated herein by reference. Temporal processing methods, such as narrowband filtering of the surface NMR signal, may distort the NMR signal itself and are ineffective when the frequency band of the noise process coincides with the desired surface NMR signal.